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https://issues.apache.org/jira/browse/CARBONDATA-3254?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bo Xu updated CARBONDATA-3254:
------------------------------
Description:
More and more people use big data to optimize their algorithm, train
their model, deploy their model as service and inference image. It's big
challenge to storage, manage and analysis lots of structured and unstructured
data, especially unstructured data, like image, video, audio and so on.
Many users use python to install their project for these scenario. Apache
CarbonData is an indexed columnar data store solution for fast analytics on big
data platform. Apache CarbonData has many great feature and high performance to
storage, manage and analysis big data. Apache CarbonData not only already
supported String, Int, Double, Boolean, Char,Date, TImeStamp data types, but
also supported Binay
[(CARBONDATA-3336)|https://issues.apache.org/jira/browse/CARBONDATA-3336],
which can avoid small binary files problem and speed up S3 access performance
reach dozens or even hundreds of times, also can decrease cost of accessing OBS
by decreasing the number of calling S3 API. But it's not easy for them to use
carbon by Java/Scala/C++. So it's better to provide python interface for these
users to use CarbonData by python code
Goals:
1. Apache CarbonData should provides python interface to support to write and
read structured and unstructured data in CarbonData, like String, int and
binary data: image/voice/video. It should not dependency Apache Spark.
2. Apache CarbonData should provides python interface to support deep learning
framework to ready and write data from/to CarbonData, like TensorFlow , MXNet,
PyTorch and so on. It should not dependency Apache Spark.
3. Apache CarbonData should provides python interface to manage and analysis
data based on Apache Spark. Apache CarbonData should support DDL, DML, DataMap
feature in Python.
was:
More and more people use big data to optimize their algorithm, train
their model, deploy their model as service and inference image. It's big
challenge to storage, manage and analysis lots of structured and unstructured
data, especially unstructured data, like image, video, audio and so on.
Many users use python to install their project for these scenario. Apache
CarbonData is an indexed columnar data store solution for fast analytics on big
data platform. Apache CarbonData is an indexed columnar data store solution for
fast analytics on big data platform. Apache CarbonData has many great feature
and high performance to storage, manage and analysis big data. Apache
CarbonData not only already supported String, Int, Double, Boolean, Char,Date,
TImeStamp data types, but also supported Binay
[(CARBONDATA-3336)|https://issues.apache.org/jira/browse/CARBONDATA-3336],
which can avoid small binary files problem and speed up S3 access performance
reach dozens or even hundreds of times, also can decrease cost of accessing OBS
by decreasing the number of calling S3 API. But it's not easy for them to use
carbon by Java/Scala/C++. So it's better to provide python interface for these
users to use CarbonData by python code
Goals:
1. Apache CarbonData should provides python interface to support to write and
read structured and unstructured data in CarbonData, like String, int and
binary data: image/voice/video. It should not dependency Apache Spark.
2. Apache CarbonData should provides python interface to support deep learning
framework to ready and write data from/to CarbonData, like TensorFlow , MXNet,
PyTorch and so on. It should not dependency Apache Spark.
3. Apache CarbonData should provides python interface to manage and analysis
data based on Apache Spark. Apache CarbonData should support DDL, DML, DataMap
feature in Python.
> PyCarbon: provide python interface for users to use CarbonData by python code
> -----------------------------------------------------------------------------
>
> Key: CARBONDATA-3254
> URL: https://issues.apache.org/jira/browse/CARBONDATA-3254
> Project: CarbonData
> Issue Type: New Feature
> Reporter: Bo Xu
> Assignee: Bo Xu
> Priority: Major
>
> More and more people use big data to optimize their algorithm, train
> their model, deploy their model as service and inference image. It's big
> challenge to storage, manage and analysis lots of structured and unstructured
> data, especially unstructured data, like image, video, audio and so on.
> Many users use python to install their project for these scenario.
> Apache CarbonData is an indexed columnar data store solution for fast
> analytics on big data platform. Apache CarbonData has many great feature and
> high performance to storage, manage and analysis big data. Apache CarbonData
> not only already supported String, Int, Double, Boolean, Char,Date, TImeStamp
> data types, but also supported Binay
> [(CARBONDATA-3336)|https://issues.apache.org/jira/browse/CARBONDATA-3336],
> which can avoid small binary files problem and speed up S3 access performance
> reach dozens or even hundreds of times, also can decrease cost of accessing
> OBS by decreasing the number of calling S3 API. But it's not easy for them to
> use carbon by Java/Scala/C++. So it's better to provide python interface for
> these users to use CarbonData by python code
> Goals:
> 1. Apache CarbonData should provides python interface to support to write and
> read structured and unstructured data in CarbonData, like String, int and
> binary data: image/voice/video. It should not dependency Apache Spark.
> 2. Apache CarbonData should provides python interface to support deep
> learning framework to ready and write data from/to CarbonData, like
> TensorFlow , MXNet, PyTorch and so on. It should not dependency Apache Spark.
> 3. Apache CarbonData should provides python interface to manage and analysis
> data based on Apache Spark. Apache CarbonData should support DDL, DML,
> DataMap feature in Python.
>
>
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